Authors: Wungrak Choi, Jin-Ok Choi, Min Kyung Chae, Min Seok Kim, Chan Yun Kim
Categories: Article, Retinal ganglion cell, Vascular endothelial growth factor, Bevacizumab, Sorafenib, Glaucoma, Diseases, Eye diseases, Ocular hypertension, Optic nerve diseases, Retinal diseases
Source: Scientific Reports
Authors: Wungrak Choi, Jin-Ok Choi, Min Kyung Chae, Min Seok Kim, Chan Yun Kim
This study investigates the effects of bevacizumab, a common vascular endothelial growth factor (VEGF) inhibitor, in treating ocular neovascular disorders, with a focus on its impact on retinal ganglion cell (RGC) survival. Given that bevacizumab has been associated with adverse effects on RGCs, we aimed to validate these reports, identify an alternative VEGF inhibitor with similar antiangiogenic efficacy but without detrimental effects on RGCs, and explore the underlying mechanisms. Using primary RGCs extracted from neonatal rats and human umbilical vascular endothelial cells (HUVECs), we compared the efficacy of bevacizumab with other VEGF inhibitors and assessed the apoptotic effects and cell survival pathways influenced by these treatments. Our results showed that while both sorafenib and bevacizumab exhibited potent VEGF-inhibitory effects in HUVECs, sorafenib led to significantly higher RGC survival rates compared to bevacizumab. Western blot analysis indicated that bevacizumab treatment resulted in lower Akt levels than sorafenib, and RNA sequencing revealed that the PI3K/AKT, Ras, and MAPK signaling pathways play crucial roles in RGC viability. These findings suggest that sorafenib may offer a safer and more effective alternative to bevacizumab for treating retinal diseases, with potential implications for the development of safer therapeutic approaches, particularly in conditions like glaucoma.
The online version contains supplementary material available at 10.1038/s41598-025-12199-w.
Excessive expression of vascular endothelial growth factor (VEGF) contributes to several sight-threatening eye conditions, including age-related macular degeneration and diabetic retinopathy, both of which are leading causes of blindness^1–6^. Intravitreal VEGF-inhibitor injections have effectively managed these debilitating diseases^6–8^.
In VEGF-inhibitor treatments, ophthalmologists have employed bevacizumab in an off-label capacity as an intravitreal agent for treating proliferative (neovascular) eye diseases^9^. Administration of 1.25–2.5 mg bevacizumab into the vitreous cavity has long been a common practice^9–11^.
However, the indiscriminate inhibition of VEGF throughout the retina, as typically achieved with VEGF-inhibitor therapy, may cause potential adverse effects^12–14^. Previous research has highlighted the multifaceted role of VEGF as a pro-survival factor in various cell types^15–17^.
Glaucoma, a chronic eye disease characterized by optic nerve damage primarily associated with elevated intraocular pressure (IOP), affects over 64 million individuals worldwide^18–20^. This condition remains incurable, necessitating continuous treatment upon diagnosis. Although the reduction of IOP remains the primary therapeutic approach, interventions that effectively halt the progression of glaucoma are currently unavailable. Notably, the pathology of glaucoma persists even when IOP is adequately controlled^21–23^. Addressing this enigma requires the identification of neuroprotective mechanisms capable of safeguarding retinal ganglion cells (RGCs), which constitute the pivotal pathophysiological substrate of glaucoma.
Given the increased vulnerability of RGCs to various stressors, promoting the survival of these cells is an effective therapeutic approach. Key factors regulating survival mechanisms under stressful conditions include hypoxia-inducible factor-1α, VEGF, and nitric oxide synthase^23–25^. Specifically, the expression levels of these factors increase in response to hypoxia and glaucoma^23–25^.
We have previously demonstrated the potential detrimental impact of VEGF-inhibitor therapy on RGC survival, particularly under stressful conditions^25^. Consequently, multiple rounds of VEGF-inhibitor treatments may inadvertently exacerbate glaucoma owing to excessive RGC loss.
The objectives of this study were to explore the effects of bevacizumab, a VEGF-inhibitor agent, on RGC survival and identify enhanced treatment strategies to promote RGC survival with similar antiangiogenic efficacy. The results of this study will help facilitate the development of novel therapeutic approaches for various retinal diseases, particularly those associated with glaucoma.
Sixty pregnant Sprague–Dawley rats were acquired from Orientbio Inc. (Seongnam, Korea). A total of 840 newborn rat pups (P2, P3 and P4) were humanely euthanized by decapitation to obtain sufficient RGC samples. Briefly, rat pups were leaved on ice covered with tissue paper for 30 min. Then rat pups were decapitated and eyes were pulled out and placed in HBSS. Eyes were dissected and obtain retina were used for experiments. Ethical approval for the study was obtained from the Institutional Animal Care and Use Committee of Yonsei University College of Medicine, Seoul, Korea (Approval Number: 2022-0053). All procedures involving rats were performed in accordance with the ethical guidelines outlined by the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Vision Research. Extensive measures were taken to minimize the number of animals used and to alleviate potential suffering. The study is reported in accordance with ARRIVE guidelines.
RGCs were isolated using a two-step immunopanning method as previously described^25–27^. Briefly, retinal tissues were extracted from 2 to 4-day-old newborn Sprague–Dawley rats and combined to form a mixed suspension of retinal cells. The retinal cell suspension was incubated with a rabbit anti-rat macrophage antibody (dilution 50; Fitzgerald Industries International, USA) for 5 min. Subsequently, the suspension was placed in a 10 cm Petri dish coated with goat anti-rabbit immunoglobulin G antibody (dilution 200; Southern Biotechnology Associates, USA) for 30 min.
Non-adherent cells were transferred to a second 10 cm Petri dish coated with mouse anti-rat thymocyte differentiation antigen (Thy) 1.1 antibody (dilution 50; Bio-Rad, USA) for 1 h. The cells were then incubated with anti-biotin magnetic microbeads (Miltenyi Biotec, Germany). Finally, the magnetically labeled RGCs were collected using a magnetic separation unit. All the procedures were performed simultaneously at room temperature (20–25 °C) in a laminar flow hood.
The isolated cells were cultured in Dulbecco’s modified Eagle’s medium/nutrient mixture F-12 (DMEM/F-12; catalog no. SH30023.01; HyClone Laboratories, USA) supplemented with 10% fetal bovine serum (Life Technologies, USA), 100 U/ml penicillin, and 100 µg/ml streptomycin (Life Technologies). These cells were seeded onto 12 mm glass coverslips pre-coated with poly-L-ornithine and laminin (Sigma-Aldrich, USA). The cultures were maintained at 37 °C in a humidified atmosphere containing 5% CO2 and 95% air.
The authenticity of the cultured RGCs was validated through Brn3-α (dilution 1,000, SC-8429, Santa Cruz Biotechnology, USA) immunostaining (Fig. 1).
Fig. 1Identification of retinal ganglion cells. Immunofluorescence staining was conducted on RGCs on day 2 of the culture, revealing a positive expression of the Brn3a marker (B). DAPI nuclear staining is depicted in (A), whereas the merged image is presented in Panel C, demonstrating the co-localization of Brn3a-positive RGCs with nuclear staining.
HUVECs (C2519A, LONZA, USA) were cultured in a 10 cm dish containing endothelial growth medium (EGM)-2 (CC-3162, LONZA) with EGM™-2 Single-Quots™ Supplements (CC-4176, LONZA) and incubated at 37 °C with 5% CO2 following the manufacturer’s instructions and as previously described^28^. The medium was changed every 2 and 3 days. When the cells reached approximately 70–85% confluence, they were harvested for subsequent experiments. All experiments were performed using HUVECs at passages 2 to 6 to ensure cellular consistency and viability.
Cell viability was assessed using the Cell Counting Kit-8 (CCK-8, #CK04, Dojindo Laboratories, Japan). Retinal ganglion cells (RGCs) and human umbilical vein endothelial cells (HUVECs) were seeded into 96-well plates at appropriate 6000 cells/well for RGCs and 3000 cells/well for HUVECs. The cells were incubated in culture medium at 37 °C with 5% CO₂ for 24 h. Following treatment, 10 µl of CCK-8 solution was added to each well containing 100 µl of complete medium, and the plates were incubated for an additional 2–4 h. Absorbance was then measured at 450 nm using a microplate reader, with a reference wavelength of 600 nm to correct for background noise (measurement 430–490 nm). Cell viability was calculated by subtracting the reference absorbance (600 nm) from the main absorbance (450 nm) to obtain the corrected absorbance value. The viability of treated groups was expressed as a percentage relative to the control group (untreated cells), which was set as 100%. The formula used for calculating relative cell viability \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\text{Cell}},{\text{viability}},(% ) = \left( {\frac{{A_{{450}} - A_{{600}} ({\text{sample}})}}{{A_{{450}} - A_{{600}} ({\text{control}})}}} \right) \times 100
Each condition was tested in triplicate (*n* = 3), and data were presented as mean ± standard deviation (SD). Statistical analysis was performed using one-way ANOVA followed to determine significant differences between groups. A p-value of < 0.05 was considered statistically significant. ### Western blot For the western blot, total cell lysates were obtained using a cell lysis buffer (RIPA buffer (#R2002, Biosesang, Korea) + EDTA-free Protease Inhibitor Cocktail (#11836170001, Roche Diagnostics Deutschland GmbH, Germany) + PhosSTOP (#04906845001, Roche Diagnostics Deutschland GmbH). The lysates were incubated on ice for 5 min. Subsequently, the lysates were sonicated, and the resulting cell homogenates were centrifuged at 15,000 × g for 15 min at 4 °C. Following centrifugation, the protein concentration in the supernatants was quantified using the Pierce™ Bicinchoninic Acid Protein Assay Kit (#23227, Thermo Fisher Scientific, USA). Soluble proteins (10 µg per sample) were boiled for 5 min and separated using 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Proteins were subsequently electrotransferred onto polyvinylidene fluoride membranes (#IPVH00010, Merk Millipore Ltd, Germany) with a pore size of 0.45 μm. To prevent nonspecific binding, the membranes were blocked with 5% skim milk (#115363, Merck Milliopere) in Tris-buffered saline containing 0.1% Tween 20 (TBS-T) and incubated overnight with primary anti-Akt (9272 S, Cell Signaling Technology) and anti-α-tubulin (T6199-100, MillporeSigma, Darmstadt) antibodies. These primary antibodies were diluted in a solution containing 0.1% bovine serum albumin and 0.01% sodium azide in TBS-T. The blots were washed three times with TBS-T and incubated with horseradish peroxidase-conjugated secondary antibodies (#7074 Rabbit, #7076 Mouse, Cell Signaling Technology, USA) for 1 h at room temperature (20–25 °C). The washes with TBS-T were repeated three times and the membranes were developed using a chemiluminescent agent (ECL; (# 32106, Thermo Fisher Scientific) and visualized using an Amersham ImgaeQuant800 (Cytiva, Sweden). The relative protein expression level of the individual genes for each sample was normalized against Tubulin expression. ### Flow cytometry To detect apoptosis, we utilized an Annexin V-fluorescein isothiocyanate (FITC) apoptosis kit from BioVision (Milpitas, CA, USA) following the manufacturer’s instructions. Briefly, after collagenase digestion, isolated cells were prepared for analysis. The cells were stained with Annexin V-FITC and propidium iodide (BioVision). Flow cytometry was conducted using a FACS LSR II instrument (BD Biosciences, USA). The percentage of viable cells was determined based on the proportion of Annexin V- and propidium iodide-positive cells in the samples. Flow cytometric analysis enabled identifying and quantifying apoptotic cells within the population of interest. ### Preparation of reagents and treatment scheme All reagents used in this study were prepared according to the manufacturer’s instructions and diluted to working concentrations using appropriate solvents. Bevacizumab (Avastin^®^, Roche) was provided as a 25 mg/ml stock solution and used at a final concentration of 2 mg/ml without further dilution. Sorafenib (Sigma) was dissolved in DMSO to obtain a 2 mM stock and diluted to 0.5 µM for experiments. Recombinant human VEGF (R&D Systems) was reconstituted to 1 µg/ml in sterile PBS and diluted to a final working concentration of 0.5 ng/ml. Pazopanib (Sigma) was prepared at 28.5 mM in DMSO and used at 28.5 µM. Selumetinib, trametinib, and vemurafenib (all from Santa Cruz) were each dissolved in DMSO at 20 mM and used at final concentrations of 20 µM (selumetinib and vemurafenib) and 16 µM (trametinib), respectively. For treatment, primary RGCs and HUVECs were seeded and stabilized for 24 h, followed by exposure to VEGF (0.5 ng/ml) for 4 h. Subsequently, cells were treated with individual VEGF inhibitors at the concentrations stated above for 24 h. Experimental conditions control (no treatment), VEGF alone, VEGF + bevacizumab, and VEGF + each VEGF inhibitor. A schematic diagram illustrating the treatment timeline and grouping is provided in Supplementary Figure S2. ### Lactate dehydrogenase assay A lactate dehydrogenase (LDH) cell cytotoxicity kit, specifically the CytoTox 96^®^ Non-Radioactive Cytotoxicity Assay Kit from Promega Corporation (Madison, USA), was utilized to assess cell survival quantitatively. Briefly, RGCs were cultured with various VEGF inhibitors. The cells were incubated with LDH detection buffer for 30 min at room temperature in the dark. A stop solution was added to terminate the reaction. Absorbance was measured at 490 nm using a microplate reader (Bio-Rad). LDH release, which indicates cytotoxicity, was calculated by dividing the experimental time point values by the maximum LDH release values and multiplying by 100. Maximum LDH release values were obtained by subjecting each culture to a freeze–thaw process, inducing nearly complete cell damage. ### Cell counting RGC death was induced by treatment with various VEGF inhibitors. After treatment, cells were fixed with 4% paraformaldehyde (#BPP-9004, T&I, Korea) for 30 min at room temperature (20–25 °C) and washed thoroughly three times with phosphate-buffered saline (PBS). For nuclear staining, cells were incubated with DAPI solution (#H-1200, Vector Laboratories, Inc., United States) for 5 min at room temperature, followed by three washes with PBS to remove excess stain. DAPI-stained RGCs were visualized using a confocal laser scanning microscope (LSM700; Carl Zeiss, Germany) equipped with a 405 nm laser for DAPI excitation. Images were captured at 400× magnification. For each experimental condition, five non-overlapping random fields were imaged per sample to ensure representative sampling. ### RNA sequencing RNA library preparation and sequencing were performed by LAS Inc. (Gimpo, Korea; [http://www.lascience.co.kr/](http://www.lascience.co.kr/)) using the SMARTER Stranded Total RNA-seq kit-v2—Pico Input Mammalian (Takara Bio, USA) in accordance with the manufacturer’s protocol. This process involved ligating RNAs with 3ʹ and 5ʹ adaptors and reverse transcribing them into cDNA. Polymerase chain reaction (PCR) was performed using different Illumina index primers to distinguish multiple time points after injury in both the proximal and distal segments. All libraries with 75 bp paired-end reads were sequenced on a NextSeq 500 System (Illumina, USA). Quality control of the reads was conducted using FastQC v0.11.5, and any sequencing adapters and low-quality bases in the raw reads were trimmed using Skewer version 0.2.2. The resulting high-quality reads were mapped to the reference genome using STAR version 2.6 software. The mapped reads were quantified as gene expression values relative to the reference genome using Cuffquant in Cufflinks version 2.2.1. Gene annotation from the reference genome rn6 (UCSC genome, [https://genome.ucsc.edu](https://genome.ucsc.edu)) in GTF format was used for gene models, and expression values were calculated as fragments per kilobase of transcripts per million mapped reads (FPKM). Differential gene expression analysis among the four selected biological conditions (RGCs versus RGCs with VEGF treatment versus RGCs with Bevacizumab treatment versus RGCs with Sorafenib treatment) was conducted using Cuffdiff within the Cufflinks package. Genes with a fold change cutoff of 2 and a p-value cutoff of 0.05 were identified as differentially expressed. A few hundred differentially expressed genes (DEGs) normalized expression values were subjected to unsupervised clustering using R scripts provided by LAS Inc. to compare the expression profiles among samples. Scatter plots for gene expression values, volcano plots for expression fold changes, and p-values between two selected samples were also generated. A gene set overlapping test between the analyzed DEGs and functionally categorized genes, encompassing the biological processes of Gene Ontology (GO), KEGG pathways, and other functional gene sets, was performed using Profiler2 version 0.2.0 to gain insights into the biological functional roles of the DEGs. ### Network analysis and visualization Functional analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) bioinformatics platform ([http://david.abcc.ncifcrf.gov](http://david.abcc.ncifcrf.gov)) and Ingenuity Pathway Analysis. GO enrichment analysis explored the associations between significantly expressed genes and their respective cellular compartments, biological processes, and molecular functions. Statistical significance was determined within DAVID using LPEseq (Seoul, Korea)^29^ to generate corrected q-values. Differential gene expression analysis was performed using the |log2FC| >1 criteria and q-value < 0.05. Only terms with a corrected q-value < 0.05 were considered statistically significant. The top list of DEGs was input into the STRING database to identify protein–protein interactions (PPIs) using a medium confidence threshold of 0.400. These interactions were subsequently visualized using Cytoscape 2.8.3 ([http://www.cytoscape.org](http://www.cytoscape.org)). Candidate genes were identified using MCODE to establish clusters. Key biological processes and pathways associated with the clusters of genes within a functionally grouped network were visualized using ClueGo/CluePedia and KEGGscape plugins. ### Quantitative reverse-transcription polymerase chain reaction (RT-qPCR) and RNA-Seq data validation RNA was isolated using an RNeasy Micro Kit (Qiagen, Germany) and reverse transcribed into complementary DNA (cDNA) using EcoDry™ Premix (Takara Bio). Real-time PCR was conducted utilizing SYBR^®^ Premix Ex Taq™ (Takara Bio) and predesigned primers (Table 1) on the StepOnePlus™ Real-Time PCR System (Applied Biosystems/Thermo Fisher Scientific). Gene expression levels were quantified using the comparative cycle threshold method and normalized to β-actin as an internal control within the same sample. Table 1Primers for quantitative reverse-transcription polymerase chain reaction.GeneSequence (5′–3′)Primers *rCar4* ATCTGCCCACCCAGTACAAGFAGCCCTCGTTTACCTCGTTTR *rLama2* TCACGCTGTCAAGGATTCAGFTTGACTTCTGGCCTTGCTTTR *rHgf* CGAGCTATCGCGGTAAAGACFTGTAGCTTTCACCGTTGCAGR *rVegfc* AGCAGCCACAAACACCTTCTFTGCTGAGGTAACCTGTGCTGR *rFgf2* GAACCGGTACCTGGCTATGAFCCGTTTTGGATCCGAGTTTAR *rFgf4* AGGCTGCGGAGACTCTACTGFACTCCGAAGATGCTCACCACR *rFgf7* GCTCTACAGACCGTGCTTCCFCCCCTCCTTCCATGTAGTCAR *rScx* ACATTTCTCACCTGGGCAACFCGTCTCTGGCCAGTGGTAGTR *rPak2* GCTGTGCTGGATGTCTTGAAFCTGACCCCTTGGTGTTCAGTR *rGfap* AGAAAACCGCATCACCATTCFTCCTTAATGACCTCGCCATCR *rRtn4r* GGCTGCCAGTGACTTAGAGGFTGAGTGCATTTCCAGCAGACR *rCdh17* CAAAGCAGAAAACCCTGAGCFGGGGAAATACAGGCACTTCAR *rWt1* GCCTTCACCTTGCACTTCTCFGACCGTGCTGTATCCTTGGTR *rEwsr1* ACTTCGCCTGGAGAACAGAAFTCCATGAGTCCACCTCTTCCR ### siRNA transfection Cells were transiently transfected with 200 nM siRNA targeting Akt and non-targeting siRNA using Lipofectamine 2000 in accordance with the manufacturer’s guidelines. Akt knockdown efficacy following siRNA transfection was assessed using a western blot. After a 48 h transfection period, the cells were harvested in six-well plates to evaluate Akt protein levels and their functional impact. #### Statistical analysis In adherence to rigorous scientific standards, all experiments were conducted in triplicate to ensure data accuracy and reliability, and their results are presented as the mean ± standard deviation. A robust statistical approach was employed to assess the significance of the observed differences between groups. Student’s *t*-test and one-way analysis of variance were used for initial group comparisons. A linear mixed model was employed to show statistically significant trends. All statistical analyses were performed using GraphPad Prism version 9.0 for Windows (GraphPad Software, USA), SPSS V22.0 software (SPSS, USA), SAS version 9.4 (SAS Institute Inc., USA), and the R package (version 4.3.0, packages; survival; The R Project for Statistical Computing, Vienna, Austria). Statistical significance was considered at *p* < 0.05, ensuring the utmost reliability in our findings, in line with the highest standards of medical research. ## Results ### Effects of VEGF and bevacizumab on RGC survival An in vitro experiment was conducted to assess the effects of VEGF and bevacizumab on RGCs. RGCs were cultured with different concentrations of VEGF (0.1, 0.5, 1, 5, and 10 ng/mL) and bevacizumab (0.1, 1, 2,5, and 10 mg/mL) for 24 h, and their viability was subsequently compared with that of RGCs cultured without these agents (control group). The viability of RGCs exposed to the various VEGF concentrations did not significantly differ from that of the control group (*p* > 0.05, Fig. 2A). Fig. 2Effects of VEGF and bevacizumab on RGC survival. RGCs were cultured with VEGF and bevacizumab for 24 h, and their viability was subsequently compared with that of RGCs cultured without these agents (control group). (**A**) The viability of RGCs cultured with various concentrations (0.1, 0.5, 1, 5, and 10 mg/mL) of VEGF did not significantly differ from that of the control group (*p* > 0.05). (**B**) The viability of RGCs cultured with 1, 2, 5, and 10 mg/ml of bevacizumab was significantly lower than that of the control group (*p* < 0.05). A linear mixed model was employed to analyze the dose effect of bevacizumab, revealing a statistically significant trend (*p* < 0.001). (**C**) Immunostaining for Brn3a revealed that RGCs cultured with 1 and 2 mg/ml bevacizumab exhibited significantly lower cell counts than the control group (**p* < 0.05, ***p* < 0.01, ****p* < 0.001, †††*p* < 0.001, *****p* < 0.0001). Although the viability of RGCs cultured with 0.1 mg/ml bevacizumab was not significantly altered compared with that of the control group, the viability of the cells cultured with 1, 2, 5, and 10 mg/ml bevacizumab was significantly lower than that of the control group (*p* < 0.05; Fig. 2B). A linear mixed model was employed to analyze the dose effect of bevacizumab, revealing a statistically significant trend (*p* < 0.001; Fig. 2B). These findings were corroborated through immunostaining for Brn3a, which revealed a similar trend. Compared with the control group, RGCs cultured with 1 and 2 mg/ml of bevacizumab had a lower cell count (Fig. 2C). ### Effect of bevacizumab on the Akt pathway To elucidate the mechanisms of action of bevacizumab on RGC survival, we examined the effects of 0.5, 1.0, and 2.0 mg/ml of bevacizumab on signaling molecules involved in pro-survival pathways, such as Akt. The Akt expression level was measured 24 h after bevacizumab treatment. Western blot analysis revealed that Akt levels gradually decreased with increasing bevacizumab concentrations (Fig. 3). Fig. 3Effect of bevacizumab on Akt. To elucidate the mechanisms of action of bevacizumab on RGC survival, we investigated the effects of different concentrations (0.5, 1.0, and 2.0 mg/mL) of bevacizumab on pivotal signaling molecules associated with pro-survival pathways, notably Akt. Western blot analysis revealed a progressive decline in Akt levels as the concentration of bevacizumab increased (***p* < 0.01, ****p* < 0.001). ### Effects of various VEGF inhibitors on RGC survival To identify a VEGF inhibitor with a lower neurotoxic profile compared to bevacizumab, we evaluated the effects of several VEGF pathway inhibitors—sorafenib, regorafenib, trametinib, vemurafenib, selumetinib, and pazopanib—on RGC viability. These inhibitors were selected based on their known roles in VEGF-related signaling or anti-angiogenic pathways. The working concentrations were determined based on preliminary HUVEC viability assays, selecting doses that exhibited similar or slightly lower apoptotic potency compared to 2 mg/ml bevacizumab. Specifically, RGCs were pretreated with VEGF (0.5 ng/ml) to mimic a pro-survival environment, and subsequently co-treated with each VEGF inhibitor. Among the tested inhibitors, sorafenib resulted in the most significantly higher RGC survival rate compared to bevacizumab under VEGF-supplemented conditions (Fig. 4). Fig. 4Effects of various VEGF inhibitors on RGC survival. To identify a VEGF inhibitor with reduced neurotoxicity compared to bevacizumab, we evaluated multiple inhibitors—sorafenib, regorafenib, trametinib, vemurafenib, selumetinib, and pazopanib—selected based on their known involvement in VEGF or related signaling pathways. RGCs were pretreated with VEGF (0.5 ng/ml) for 4 h and then co-treated with each VEGF inhibitor at concentrations determined by preliminary HUVEC screening. Cell viability was assessed after 24 h. Among the inhibitors tested, sorafenib significantly improved RGC viability compared to bevacizumab. Asterisks above column denote statistical significance compared to the bevacizumab-treated group ( *****p* < 0.0001). ### Effects of sorafenib and bevacizumab on RGC survival We comprehensively assessed the effects of different concentrations of sorafenib (0.1, 0.5, 1.0, 2.0, 5.0, and 10.0 µM) and bevacizumab (0.1, 1.0, 2.0, 5.0, and 10.0 mg/mL) on RGC survival using cell viability and LDH assays. The viability of RGCs was significantly decreased following treatment with bevacizumab and sorafenib in a dose-dependent manner, starting at 1.0 mg/ml and 0.5 µM, respectively (*p* < 0.001; Fig. 5A). Consistently, LDH assay results revealed that LDH release was notably increased following treatment with bevacizumab and sorafenib in a dose-dependent manner, starting at 1.0 mg/ml and 2.0 µM, respectively (*p* < 0.001; Fig. 5B). Fig. 5Effects of sorafenib and bevacizumab on RGC survival. We comprehensively assessed the effects of different concentrations of sorafenib (0.1, 0.5, 1.0, 2.0, 5.0, and 10.0 µM) and bevacizumab (0.1, 1.0, 2.0, 5.0, and 10.0 mg/mL) on RGC survival using cell viability and LDH assays. The viability of RGCs was significantly decreased following treatment with bevacizumab and sorafenib in a dose-dependent manner, starting at 1.0 mg/ml and 0.5 µM, respectively (**A**). Concurrently, LDH assay results demonstrated that LDH release increased dose-dependently following treatment with bevacizumab and sorafenib, starting at 1.0 mg/ml and 2.0 µM, respectively (**B**). A linear mixed model was employed to analyze the dose effect of bevacizumab and sorafenib, revealing a statistically significant trend (**p* < 0.05, ***p* < 0.01, ****p* < 0.001, †††*p* < 0.001, *****p* < 0.0001). ### HUVEC survival To investigate the effects of VEGF inhibitors on vascular cells, we assessed the effects of various concentrations of sorafenib (0.1–5.0 µM) and bevacizumab (0.1–10.0 mg/mL) on the viability of HUVECs. Cell viability assay results showed that the viability of HUVECs was significantly decreased by bevacizumab and sorafenib in a dose-dependent manner, starting at 2.0 mg/ml and 0.5 µM, respectively (Fig. 6A). Fig. 6Human umbilical vein endothelial cell (HUVEC) survival. In the cell viability assay, various concentrations of bevacizumab (0.1–10.0 mg/mL) and sorafenib (0.1–5.0 µM) were used. The viability of HUVECs was significantly decreased by bevacizumab and sorafenib in a dose-dependent manner, starting at 2.0 mg/ml and 0.5 µM, respectively (**A**). Flow cytometry analysis demonstrated that 0.5 µM sorafenib exhibited a similar or superior apoptotic effect to 2.0 mg/ml bevacizumab on HUVECs (**B**). Consistently, immunostaining indicated a lower cell count after treatment with 0.5 µM sorafenib than with 2.0 mg/ml bevacizumab (**C**) (**p* < 0.05, ***p* < 0.01, ****p* < 0.001, *****p* < 0.0001). We assessed live and dead cells through flow cytometry to further validate these findings. The flow cytometry results confirmed those of the cell viability assay, and 0.5 µM sorafenib exhibited a similar or even superior apoptotic effect to 2.0 mg/ml bevacizumab on HUVECs (Fig. 6B). These results were also corroborated through immunostaining. Specifically, the cell count was lower after treatment with 0.5 µM sorafenib than 2.0 mg/ml bevacizumab (Fig. 6C). ### Effects of sorafenib and bevacizumab on RGC Akt We investigated the effects of 2.0 mg/ml bevacizumab and 0.5 µM sorafenib on signaling molecules associated with pro-survival pathways, specifically Akt, in RGCs. Western blot analysis revealed that Akt levels significantly increased after VEGF treatment. However, Akt levels were markedly lower after treatment with 2.0 mg/ml bevacizumab than with 0.5 µM sorafenib, indicating the differential effects of these agents on Akt signaling (Fig. 7A). We used the siRNA method to corroborate these findings and observed consistent results (Fig. 7B). Fig. 7Effects of sorafenib and bevacizumab on RGC Akt. We examined the effects of 2.0 mg/ml bevacizumab and 0.5 µM sorafenib on Akt signaling in RGCs. Akt was measured 24 h after bevacizumab treatment. Western blot analysis revealed that Akt levels significantly increased after VEGF treatment. Notably, Akt levels were markedly lower after treatment with 2.0 mg/ml bevacizumab than with 0.5 µM sorafenib, indicating the differing impacts of the two VEGF inhibitors on Akt signaling (**A**). To validate these findings, the siRNA method was used and yielded consistent results (**B**) (**p* < 0.05, ***p* < 0.01, ****p* < 0.001, *****p* < 0.0001). ### Effects of treatment with 0.5 µM sorafenib and 2 mg/ml bevacizumab on RGC survival The effects of 2.0 mg/ml bevacizumab and 0.5 µM sorafenib on the survival of RGCs were evaluated. Results of advanced flow cytometry showed that the survival rate of RGCs substantially increased after VEGF treatment. However, the survival rate of RGCs was significantly lower after treatment with 2.0 mg/ml bevacizumab than with 0.5 µM sorafenib, indicating the distinct effects of these agents on RGC viability (Fig. 8A). The observed results were confirmed through a tunnel assay (Fig. 8B). Fig. 8Effects of treatment with 0.5 µM sorafenib and 2 mg/ml bevacizumab on RGC survival. We assessed the effects of 2.0 mg/ml bevacizumab and 0.5 µM sorafenib on RGC survival. Results of advanced flow cytometry showed that the survival rate of RGCs substantially increased after VEGF treatment. However, the survival rates of RGCs were significantly lower after treatment with 2.0 mg/ml bevacizumab than with 0.5 µM sorafenib, indicating the distinct effects of these agents on RGC viability (**A**). These results were further validated using a tunnel assay (**B**) (**p* < 0.05, *****p* < 0.0001). ### RNA sequencing results We conducted comprehensive RNA sequencing to unravel gene expression discrepancies and delineate the specific cellular pathways influenced by VEGF-inhibitor treatment. After a 24 h stabilization period, isolated RGCs were subjected to four distinct control (RGCs only), VEGF treatment, 2.0 mg/ml bevacizumab treatment, and 0.5 µM sorafenib treatment. RNA sequencing was then performed. The initial analysis results showed that VEGF-inhibitor treatment modified the gene expression profiles of RGCs (Fig. 9A,B). Fig. 9RNA sequencing results. We conducted an RNA sequencing study after a 24 h stabilization period for isolated RGCs. The cells were subjected to four distinct control (RGCs only), VEGF treatment, 2.0 mg/ml bevacizumab treatment, and 0.5 µM sorafenib treatment. (**A**) Volcano plot showing the log2-fold change in gene expression after 0.5 µM sorafenib treatment. Each dot represents a single gene. (**B**) Heat map of gene expression in RGCs. (**C**) Our analytical approach focused on genes that were upregulated after VEGF treatment but downregulated after VEGF-inhibitor treatment when compared with the control group or genes that were downregulated after VEGF treatment but upregulated after VEGF-inhibitor treatment when compared with the control group. (**D**) Fourteen genes displayed a greater than two-fold change with an adjusted p-value of less than 0.05. This value was confirmed with RT-qPCR. (**p* < 0.05, ***p* < 0.01, ****p* < 0.001, *****p* < 0.0001). We focused on genes that were upregulated by VEGF treatment but downregulated by VEGF-inhibitor treatment compared with the control group or genes that were downregulated by VEGF treatment but upregulated by VEGF-inhibitor treatment compared with the control group (Fig. 9C). This stringent selection process yielded 14 genes with a greater than two-fold change and an adjusted p-value of less than 0.05 (Table 2). This value was confirmed with RT-qPCR (Fig. 9D). Table 2Genes that displayed a greater than two-fold change with an adjusted p-value of less than 0.05 in RNA sequencing.Gene symbolLog2(FC)Full descriptions of the geneVEGFBevacizumabSorafenib *Gfap* 7.3144.1703.937Glial fibrillary acidic protein [Source: RGD Symbol; Acc:2679] *Vegfc* 6.0932.3091.913Vascular endothelial growth factor C [Source: RGD Symbol; Acc:619800] *Rtn4r* 5.7592.9642.645Reticulon 4 receptor [Source: RGD Symbol; Acc:620810] *Pak2* 4.5153.1941.650P21 (RAC1) activated kinase 2 [Source: RGD Symbol; Acc:61953] *Ewsr1* 3.9711.6871.603EWS RNA-binding protein 1 [Source: RGD Symbol; Acc:1307258] *Fgf4* 3.1960.0000.000Fibroblast growth factor 4 [Source: RGD Symbol; Acc:620127] *Wt1* 3.1011.2281.153WT1 transcription factor [Source: RGD Symbol; Acc:3974] *Fgf2* 2.1450.0000.779Fibroblast growth factor 2 [Source: RGD Symbol; Acc:2609] *Fgf7* 1.5011.3750.772Fibroblast growth factor 7 [Source: RGD Symbol; Acc:61805] *Scx* 1.3132.3190.000Scleraxis bHLH transcription factor [Source: RGD Symbol; Acc:1588254] *Car4* 1.1700.5230.233Carbonic anhydrase 4 [Source: RGD Symbol; Acc:2242] *Cdh17* 1.1412.4360.525Cadherin 17 [Source: RGD Symbol; Acc:619748] *Lama2* 0.9940.3800.236Laminin subunit alpha 2 [Source: RGD Symbol; Acc:1308889] *Hgf* 0.9472.3130.390Hepatocyte growth factor [Source: RGD Symbol; Acc:2794] ### Pathway analysis Functional analysis was conducted using the DAVID bioinformatics package to gain deeper insights into the biological relevance of the identified genes. GO enrichment analysis explored the associations between significantly expressed genes and their cellular compartments, biological processes, and molecular functions. The top DEGs were then subjected to the STRING database to elucidate PPIs, employing a medium confidence threshold of 0.400. These interactions were subsequently visualized using Cytoscape software, wherein the genes were organized into functionally grouped networks. In this network, the inner circles indicate the effects of the VEGF inhibitors on specific genes, with blue representing the effect of sorafenib, purple that of bevacizumab, and yellow that of both inhibitors (Fig. 10). Fig. 10Pathway analysis. Inner circles indicate the effects of specific genes related to VEGF-inhibitor treatment, with blue representing the effect of sorafenib, purple that of bevacizumab, and yellow that of both sorafenib and bevacizumab. Outer circles represent well established survival pathways, with orange highlighting the PI3-Akt signaling pathway, purple the Ras signaling pathway, red the MAPK signaling pathway, and green the JAK-STAT signaling pathway. Our analysis unveiled the significant involvement of the PI3-Akt, Ras, and MAPK signaling pathways in the context of our study. However, genes associated with the JAK-STAT pathway showed no significant involvement in our investigation. The outer circles denote common survival pathways, with orange highlighting the PI3-Akt signaling pathway, purple the Ras signaling pathway, red the MAPK signaling pathway, and green the JAK-STAT signaling pathway. Interestingly, our analysis revealed significant involvement of the PI3-Akt, Ras, and MAPK signaling pathways in the context of our study. However, genes associated with the JAK-STAT pathway showed no significant participation. ## Discussion The present study investigated the effects of VEGF inhibitors, particularly bevacizumab and sorafenib, on the survival of RGCs and their mechanisms of action. First, our findings revealed that bevacizumab exhibited RGC toxicity, necessitating carefully considering its use. Second, administration of bevacizumab to RGCs disrupted the PI3-Akt pathway. Third, compared with bevacizumab, sorafenib exerted a milder effect on the PI3-Akt pathway and less toxicity to RGCs while maintaining a similar apoptotic effect on vascular endothelial cells. These results suggest the possibility of an alternative approach that preserves the effects of VEGF inhibitors on the retina while protecting RGCs. Bevacizumab, a monoclonal antibody specifically designed to target VEGF, has attracted significant attention as a potential treatment modality for retinal diseases characterized by abnormal blood vessel growth^9,11^. These conditions include age-related macular degeneration (AMD), diabetic retinopathy, and retinal vein occlusion, all characterized by the pathological formation of blood vessels within the retina. One critical aspect of bevacizumab use in the context of retinal diseases is its potential effect on RGCs, which play a fundamental role in visual function. RGCs transmit visual information from the retina to the brain, making their health and survival pivotal for maintaining normal vision^30,31^. Several issues have been associated with using bevacizumab in relation to RGCs. For instance, the potential toxicity of bevacizumab to RGCs could jeopardize the health and proper functioning of RGCs, resulting in visual impairment or exacerbation of existing visual deficits^32–35^. This may be even more dangerous for patients with glaucoma^36,37^. Glaucoma encompasses a group of eye diseases characterized by their detrimental effects on the optic nerve, specifically targeting the RGCs responsible for transmitting crucial visual information from the eye to the brain^38^. The genesis of this damage is often attributed to elevated IOP, which exerts deleterious pressure on these RGCs, leading to their degeneration and consequential harm to the optic nerve. This process is typically insidious and progressive, initially manifesting as peripheral (side) vision impairment. If left untreated, it may culminate in complete blindness. Glaucoma is a chronic condition and a leading cause of blindness globally^20,39^. Regular eye examinations are indispensable, especially for individuals at risk or those with a family history of glaucoma, as they facilitate early detection and intervention. Timely management is crucial because it can effectively slow down or prevent vision loss from damage to the RGCs and optic nerve. Glaucoma is a non-reversible condition, making the preservation of RGCs a paramount concern in the management of this disease^39^. Evidence suggests that injecting VEGF inhibitors, particularly bevacizumab, can contribute to RGC damage in patients with glaucoma^33,35–37^. The vulnerability of RGCs in glaucoma is well established because these cells play a pivotal role in transmitting visual information from the eye to the brain. Elevated IOP, a hallmark of glaucoma, places significant stress on RGCs, ultimately leading to their degeneration and consequent damage to the optic nerve. Although effective in controlling abnormal blood vessel growth in various eye conditions, VEGF-inhibitor therapy may inadvertently exert adverse effects on RGCs. The potential RGC damage because of anti-VEGF injections, including bevacizumab, underscores the need for careful consideration when selecting treatment options for patients with glaucoma. Balancing the benefits of VEGF-inhibitor therapy in managing glaucoma with its potential impact on RGCs remains a critical aspect of glaucoma care and requires ongoing research and clinical vigilance. RGC damage associated with anti-VEGF injections, particularly bevacizumab, appears to stem from multiple factors. First, IOP increases after VEGF-inhibitor injections^40,41^. This elevated IOP can place additional stress on RGCs, exacerbating their vulnerability and contributing to damage. Second, bevacizumab exhibits RGC toxicity^32,33^. The specific mechanisms underlying this toxicity are an area of ongoing research, but the direct impact of the drug on RGCs can lead to their impairment and potential degeneration. Collectively, these factors highlight the complex relationship between VEGF-inhibitor therapy and RGC damage. Although VEGF-inhibitor injections have shown efficacy in managing various eye conditions, their potential adverse effects on RGCs underscore the importance of careful patient monitoring and individualized treatment approaches to mitigate the risk of further harm to these critical retinal cells. Numerous studies have investigated the molecules involved in promoting the survival of RGCs. Among these are nerve growth factor, brain-derived neurotrophic factor, ciliary neurotrophic factor, VEGF, and insulin-like growth factors^25,42–44^. VEGF is a glycoprotein with a molecular weight of 46 kDa that binds to receptors on the surface of vascular endothelial cells, stimulating their proliferation and increasing capillary permeability^45,46^. This factor promotes the development and maturation of neural tissues, including the retina^4,47^. During development, VEGF is expressed by various cell types in the retina, such as astrocytes in the RGC layer, inner nuclear layer cells, Müller cells, and retinal pigment epithelial cells^4,48,49^. Even in the mature retina, VEGF is expressed without active neovascularization and is implicated in the maintenance and function of adult retinal neuronal cells^49^. Moreover, VEGF exerts neuroprotective effects, particularly in safeguarding injured RGCs and slowing down their degeneration post-axotomy^50^. Our previous research confirmed that VEGF promotes the survival of RGCs under hypoxic conditions^25^. In this study, when VEGF activation was hindered with bevacizumab after 4 h of hypoxia, the RGC survival rate dose-dependently decreased^25^. Collectively, these findings emphasize the critical role of VEGF in supporting the survival of RGCs. An excessive reduction in VEGF levels because of bevacizumab treatment may result in unintended damage to RGCs. Hence, balancing the therapeutic benefits of VEGF modulation with its potential consequences for RGC health is a key consideration in managing retinal conditions. Intravitreal injections of VEGF inhibitors, notably bevacizumab, have been used in clinical settings because of their cost-effectiveness. However, our study and previous studies raised concerns about the potential risks associated with repeated VEGF-inhibitor injections, particularly their interference with the neuroprotective actions of VEGF. Although some studies have suggested the safety of bevacizumab treatment for RGCs, future studies should explore the potential side effects, including serious eye conditions such as glaucoma, of multiple bevacizumab injections. In light of these considerations, alternative treatments for ischemic retinal conditions, such as AMD, retinal vein occlusion, and proliferative diabetic retinopathy, must be developed. The present study evaluated the effects of various VEGF inhibitors to identify alternatives that might offer better safety profiles compared with bevacizumab. Our findings suggest that sorafenib, a multi-kinase inhibitor, can replace bevacizumab. Indeed, sorafenib demonstrated effective VEGF-inhibitor activity in vascular endothelial cells while causing less damage to RGCs. These promising results suggest that sorafenib could be a safe and viable alternative to bevacizumab for treating ischemic retinal conditions. Further research and clinical studies are warranted to validate these findings and determine the full scope of the efficacy and safety of sorafenib in the treatment of various retinal diseases. Such investigations will guide clinicians in making informed treatment decisions and providing better options for patients seeking optimal care for their eye conditions. Sorafenib is a kinase inhibitor approved for the treatment of various conditions, including advanced renal cell carcinoma, hepatocellular carcinoma, certain types of acute myeloid leukemia, and advanced thyroid carcinoma that does not respond to radioactive iodine treatment^51,52^. This drug affects several protein kinases, including the VEGF receptor, platelet-derived growth factor (PDGF) receptor, and rapidly accelerated fibrosarcoma (RAF) kinases^51,52^. Initially identified as an RAF kinase inhibitor, sorafenib’s action extends to inhibiting multiple receptor tyrosine kinases involved in angiogenesis, the new blood vessel formation process^51,52^. Its anti-proliferative and antiangiogenic properties are derived from its ability to block the RAF/mitogen-activated protein (MAP)/extracellular signal-regulated kinase (ERK) kinase cascade and its impact on receptor tyrosine kinases, including VEGF receptor 2 (VEGFR2), VEGFR3, PDGF receptor, FLT3, Ret, and c-Kit^51,52^. Additionally, sorafenib interacts with hypoxia-inducible factors 1 and 2, influencing the expression of growth factors such as VEGF and PDGF^51,52^. In the context of ocular health, a prior study examined the potential of sorafenib to counteract the overexpression of VEGF, PDGF, and PlGF in human retinal pigment epithelial cells subjected to light-induced stress^53^. The authors presented the promising viability of sorafenib as an antiangiogenic treatment for AMD^53^. Moreover, various in vitro studies have explored the effects of sorafenib. Sorafenib administration to primary human optic nerve head astrocytes and primary human retinal pigment epithelial cells under white light exposure can significantly reduce the light-induced overexpression of VEGF^54,55^. In the rat oxygen-induced retinopathy model, sorafenib could inhibit retinal neovascularization dose-dependently^56^. These findings strongly suggest sorafenib as a potentially effective therapeutic approach for patients with retinal diseases, specifically, AMD, aligning closely with the results of the current study. These findings offer hope for advancements in treatment options and improved outcomes in managing this complex and challenging retinal condition. Nonetheless, further in-depth research and rigorous clinical trials are imperative to thoroughly validate the effectiveness and safety of sorafenib for this specific application. Additional investigations are critical to translating these promising preliminary findings into established treatments that can offer substantial benefits to individuals with retinal diseases, such as AMD. To further elucidate the mechanisms underlying differential effects of VEGF inhibitors on RGC survival, we examined the expression profiles of genes significantly modulated by VEGF, bevacizumab, and sorafenib using RNA sequencing. Fourteen genes were identified as significantly altered (adjusted *p* < 0.05, fold change > 2) and validated by RT-qPCR (Fig. 9D). Several of these genes, including Gfap, Vegfc, and Pak2, are known to be associated with glial activation, angiogenesis, and cell survival pathways, respectively. Notably, Gfap (glial fibrillary acidic protein), a marker of reactive gliosis, was highly upregulated by VEGF and suppressed by both bevacizumab and sorafenib, though to differing degrees. This may reflect the modulation of glial responses by these agents. Pak2, involved in cytoskeletal dynamics and apoptosis, showed differential regulation that may relate to cell survival modulation under stress. Vegfc was also upregulated by VEGF and suppressed more by bevacizumab than sorafenib, suggesting a potential role in neurovascular cross-talk. Other genes such as Fgf2, Hgf, and Wt1 are involved in neuroprotection, growth signaling, and transcriptional regulation of survival pathways. Their relative preservation with sorafenib compared to bevacizumab may contribute to the observed differences in RGC viability. Together, these gene expression changes support the hypothesis that sorafenib induces a less disruptive transcriptomic profile in RGCs than bevacizumab and preserves neuroprotective signaling networks more effectively. We studied several candidate signaling molecules using RNA sequencing to better understand the signaling pathways downstream of VEGF. We conducted a comprehensive functional analysis using the DAVID bioinformatics package to investigate the biological significance of the identified genes. Using Cytoscape software, we also visualized the intricate web of gene interactions and relationships. This tool facilitates the organization of genes into functionally grouped networks, offering a clear and structured representation of how these genes collaborate and contribute to specific biological processes. Our investigation yielded intriguing insights into the PI3-Akt, Ras, MAPK, and JAK-STAT signaling pathways. These pathways are key components of the intricate network of signaling cascades activated by VEGF, shedding light on their critical involvement in RGC survival. Notably, our analysis unveiled the significant participation of the PI3-Akt, Ras, and MAPK signaling pathways in the context of our study. However, genes associated with the JAK-STAT pathway showed no significant involvement in our investigation. Interestingly, several genes were shared among the PI3-Akt, Ras, and MAPK pathways, whereas the JAK-STAT pathway exhibited a distinct genetic profile. This observation suggests that the JAK-STAT pathway may exhibit a comparatively independent response mechanism. Future investigations should investigate this phenomenon to understand its implications and mechanisms. To our knowledge, studies exploring the complex interplay between VEGF-inhibitor therapies and RGC survival are limited. Therefore, our findings offer novel insights into the molecular mechanisms underlying RGC survival and may guide the development of efficacious treatments for retinal diseases, potentially improving the outcomes of individuals with these conditions. This study has a few limitations that merit consideration. First, our in vitro model focused exclusively on RGCs, whereas in vivo, RGCs exist in a complex milieu alongside various other cell types, including astrocytes, Müller cells, and glial cells. Thus, this controlled environment may not accurately replicate the in vivo interactions that affect RGC survival. Second, in this study, we used RGCs derived from neonatal rats, which are commonly employed due to their high viability and experimental reproducibility. However, neonatal RGCs are more responsive to neurotrophic factors and Akt pathway activation than adult RGCs. Since anti-VEGF treatments are primarily used in adult populations, this difference limits the direct translatability of our findings. We acknowledge this as a limitation and suggest that further studies using adult RGCs or in vivo models are warranted. Third, numerous factors beyond VEGF may contribute to cell survival. Although our study examined the correlations with VEGF, a comprehensive analysis of all potential contributing factors was not performed. Additionally, our study was conducted over a relatively short incubation period (48 h) because of the various constraints of the in vitro primary RNA culture system. This limited duration may not fully capture the long-term effects and complexities of RGC survival and treatment responses. Lastly, rat RGCs may differ from human RGCs, limiting the direct extrapolation of our findings to clinical contexts. Despite these inherent limitations, our study introduces novel clinical perspectives, suggesting that sorafenib holds promise as a safe treatment option for patients. However, further experimental and clinical investigations are required to validate and substantiate our in vitro findings in real-world clinical settings. Our study indicated that sorafenib is a potentially more effective and safer treatment option than bevacizumab for various retinal diseases, uncovered new genes, and provided insights into the complex roles of multiple signaling pathways in this context. These findings will help facilitate the development of safe therapeutic approaches for managing retinal diseases associated with glaucoma. This study marks a significant advancement in the literature by improving the management and treatment outcomes for complex ocular conditions. ## Electronic supplementary material Below is the link to the electronic supplementary material. Supplementary Material 1